University of Zagreb Medical School, Croatian Institute for Brain Research, Zagreb, Croatia.
Translational neuroscience 01/2011; 2(3):256-264.
Source: PubMed

ABSTRACT Autism spectrum disorders (ASD) represent complex neurodevelopmental disorders characterized by impairments in reciprocal social interactions, abnormal development and use of language, and monotonously repetitive behaviors. With an estimated heritability of more than 90%, it is the most strongly genetically influenced psychiatric disorder of the young age. In spite of the complexity of this disorder, there has recently been much progress in the research on etiology, early diagnosing, and therapy of autism. Besides already advanced neuropathologic research, several new technological innovations, such as sleep functional MRI, diffusion tensor imaging (DTI) and proton magnetic resonance spectroscopy imaging ((1)H-MRS) divulged promising breakthroughs in exploring subtle morphological and neurochemical changes in the autistic brain. This review provides a comprehensive summary of morphological and neurochemical alterations in autism known to date, as well as a short introduction to the functional research that has begun to advance in the last decade. Finally, we mention the progress in establishing new standardized diagnostic measures and its importance in early recognition and treatment of ASD.

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    ABSTRACT: There are at least two fundamental unanswered questions in the literature on autism spectrum disorders (ASD): Are abnormalities in white (WM) and gray matter (GM) consistent with one another? Are WM morphometric alterations consistent with alterations in the GM of regions connected by these abnormal WM bundles and vice versa? The aim of this work is to bridge this gap. After selecting voxel-based morphometry and diffusion tensor imaging studies comparing autistic and normally developing groups of subjects, we conducted an activation likelihood estimation (ALE) meta-analysis to estimate consistent brain alterations in ASD. Multidimensional scaling was used to test the similarity of the results. The ALE results were then analyzed to identify the regions of concordance between GM and WM areas. We found statistically significant topological relationships between GM and WM abnormalities in ASD. The most numerous were negative concordances, found bilaterally but with a higher prevalence in the right hemisphere. Positive concordances were found in the left hemisphere. Discordances reflected the spatial distribution of negative concordances. Thus, a different hemispheric contribution emerged, possibly related to pathogenetic factors affecting the right hemisphere during early developmental stages. Besides, WM fiber tracts linking the brain structures involved in social cognition showed abnormalities, and most of them had a negative concordance with the connected GM regions. We interpreted the results in terms of altered brain networks and their role in the pervasive symptoms dramatically impairing communication and social skills in ASD patients. Hum Brain Mapp, 2013. © 2013 Wiley Periodicals, Inc.
    Human Brain Mapping 07/2013; · 6.88 Impact Factor
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    ABSTRACT: It is unclear how standardized neuropsychological measures of motor function relate to brain volumes of motor regions in autism spectrum disorder (ASD). An all-male sample composed of 59 ASD and 30 controls (ages 5-33 years) completed three measures of motor function: strength of grip (SOG), finger tapping test (FTT), and grooved pegboard test (GPT). Likewise, all participants underwent magnetic resonance imaging with region of interest (ROI) volumes obtained to include the following regions: motor cortex (precentral gyrus), somatosensory cortex (postcentral gyrus), thalamus, basal ganglia, cerebellum, and caudal middle frontal gyrus. These traditional neuropsychological measures of motor function are assumed to differ in motor complexity, with GPT requiring the most followed by FTT and SOG. Performance by ASD participants on the GPT and FTT differed significantly from that of controls, with the largest effect size differences observed on the more complex GPT task. Differences on the SOG task between the two groups were nonsignificant. Since more complex motor tasks tap more complex networks, poorer GPT performance by those with ASD may reflect less efficient motor networks. There was no gross pathology observed in classic motor areas of the brain in ASD, as ROI volumes did not differ, but FTT was negatively related to motor cortex volume in ASD. The results suggest a hierarchical motor disruption in ASD, with difficulties evident only in more complex tasks as well as a potential anomalous size-function relation in motor cortex in ASD.
    Journal of Clinical and Experimental Neuropsychology 08/2013; · 1.86 Impact Factor
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    ABSTRACT: Autism spectrum disorders (ASD) are highly heritable complex neurodevelopmental disorders with a 4:1 male: female ratio. Common genetic variation could explain 40-60% of the variance in liability to autism. Because of their small effect, genome-wide association studies (GWASs) have only identified a small number of individual single-nucleotide polymorphisms (SNPs). To increase the power of GWASs in complex disorders, methods like convergent functional genomics (CFG) have emerged to extract true association signals from noise and to identify and prioritize genes from SNPs using a scoring strategy combining statistics and functional genomics. We adapted and applied this approach to analyze data from a GWAS performed on families with multiple children affected with autism from Autism Speaks Autism Genetic Resource Exchange (AGRE). We identified a set of 133 candidate markers that were localized in or close to genes with functional relevance in ASD from a discovery population (545 multiplex families); a gender specific genetic score (GS) based on these common variants explained 1% (P = 0.01 in males) and 5% (P = 8.7 × 10(-7) in females) of genetic variance in an independent sample of multiplex families. Overall, our work demonstrates that prioritization of GWAS data based on functional genomics identified common variants associated with autism and provided additional support for a common polygenic background in autism.
    Frontiers in Genetics 01/2014; 5:33.

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